passioncipher/EHR_Analysis

create env

conda create -n EHR_Analysis_new python=3.6 -y

activate the env

conda activate EHR_Analysis_new

create requirements.txt install the Requirements

pip install -r requirements.txt

download the data from

patient = pd.read_csv('https://raw.githubusercontent.com/kthouz/Diabetes-PracticeFusion/master/agg_data/patient.csv') diagnosis = pd.read_csv('https://raw.githubusercontent.com/kthouz/Diabetes-PracticeFusion/master/agg_data/diagnosis.csv') medication = pd.read_csv('https://raw.githubusercontent.com/kthouz/Diabetes-PracticeFusion/master/agg_data/medication.csv') phy_sp = pd.read_csv('https://raw.githubusercontent.com/kthouz/Diabetes-PracticeFusion/master/agg_data/physician_specialty.csv') transcript = pd.read_csv('https://raw.githubusercontent.com/kthouz/Diabetes-PracticeFusion/master/agg_data/transcript.csv')

bash

git init

dvc init

dvc add data_given/*.csv

dvc add data_given/*.csv

git add .

git commit -m "first commit"

git add . && git commit -m "updated README.md"

How to push the code in gitHub

```buildoutcfg git remote add origin https://github.com/RajeshThakur1/EHR_Analysis.git ```

Rename your Current branch main

git branch -M main

Now push your Entire code to the main branch

git push -u origin main

In order to reproduce the all stages from dvc.yaml file excute the below command

dvc repro

In order to track that how your model is behaving use below command

 dvc metrics show

To check the difference of the performance of the model

dvc metrics diff

for testing are using tox am

create your own library

 python setup.py sdist bdist_wheel

tox command

tox

for rebuilding

tox -r

pytest

pytest -c

setup command

pip install -e .